R/deedee_venn.R

In lea-rothoerl/DeeDee: Comparative Evaluation and Visualization of Differential Expression Analyses

#' DeeDee Venn Diagram
#'
#' @description `deedee_venn` creates a Venn diagram depicting the overlaps of
#' differentially expressed genes in the input datasets.
#'
#' @param data named list of results from deedee_prepare()
#' @param mode show all overlapping DE genes (`both`, default),
#'             only conjointly up-regulated (`up`)
#'             or only conjointly down-regulated (`down`) genes
#' @param pthresh threshold for p-values to be in-/excluded (default = 0.05)
#'
#' @return ggplot object (plottable with show()/print())
#'
#' @examples
#'
#' data(DE_results_IFNg_naive, package = "DeeDee")
#' IFNg_naive <- deedee_prepare(IFNg_naive, "DESeq2")
#'
#' data(DE_results_IFNg_both, package = "DeeDee")
#' IFNg_both <- deedee_prepare(IFNg_both, "DESeq2")
#'
#' data(DE_results_Salm_naive, package = "DeeDee")
#' Salm_naive <- deedee_prepare(Salm_naive, "DESeq2")
#'
#' data(DE_results_Salm_both, package = "DeeDee")
#' Salm_both <- deedee_prepare(Salm_both, "DESeq2")
#'
#' dd_list <- list(
#'   IFNg_naive = IFNg_naive, IFNg_both = IFNg_both,
#'   Salm_naive = Salm_naive, Salm_both = Salm_both
#' )
#'
#' # deedee_venn(dd_list, pthresh = 0.05, mode = "both")
#' @export
#'

deedee_venn <- function(data,
                        mode = "both",
                        pthresh = 0.05) {

  # ----------------------------- argument check ------------------------------
  checkmate::assert_list(data, type = "data.frame", min.len = 2) # , max.len = 4)
  for (i in 1:length(data)) {
    checkmate::assert_data_frame(data[[i]], type = "numeric")
  }
  checkmate::assert_number(pthresh, lower = 0, upper = 1)
  choices <- c("up", "down", "both")
  checkmate::assert_choice(mode, choices)

  # ---------------------------- data preparation -----------------------------
  for (i in 1:length(data)) {
    data[i][[1]] <- subset(
      data[i][[1]],
      data[i][[1]]$pval < pthresh
    )

    if (length(data[i][[1]][[1]]) == 0) {
      return(NULL)
    }

    if (mode == "up") {
      data[i][[1]] <- subset(
        data[i][[1]],
        data[i][[1]]$logFC > 0
      )
    }
    if (mode == "down") {
      data[i][[1]] <- subset(
        data[i][[1]],
        data[i][[1]]$logFC < 0
      )
    }
    data[i][[1]] <- data[i][[1]]["logFC"] # removing p-value column
    colnames(data[i][[1]]) <- c(paste("logFC", i, sep = ""))
    data[i][[1]] <- as.matrix(data[i][[1]]) # conversion to matrix
    names <- rownames(data[i][[1]])
    data[i][[1]] <- as.vector(data[i][[1]]) # conversion to vector
    names(data[i][[1]]) <- names
    data[i][[1]] <- sort(data[i][[1]], decreasing = TRUE)
    data[i][[1]] <- names(data[i][[1]])
  }

  # ----------------- creation of the resulting venn diagram ------------------
  pal <- c(viridis::viridis(length(data), option = "magma"))

  res <- ggvenn::ggvenn(data,
    fill_alpha = 0.2,
    fill_color = pal,
    show_percentage = FALSE,
    stroke_color = "grey80",
    set_name_size = 4
  )

  # --------------------------------- return ----------------------------------
  return(res)
}